1. Optimized Hemodynamic Assessment to Predict Stroke Risk in Vertebrobasilar Disease: Analysis From the VERiTAS Study
- Author
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Alfred P. See, Dilip K. Pandey, Xinjian Du, Linda Rose‐Finnell, Fady T. Charbel, Colin P. Derdeyn, Sepideh Amin‐Hanjani, DeJuran Richardson, Hui Xie, Keith Thulborn, Michael P. Flanner, Hagai Ganin, Sean Ruland, Rebecca Grysiewicz, Aslam Khaja, Laura Pedelty, Fernando Testai, Archie Ong, Noam Epstein, Hurmina Muqtadar, Karriem Watson, Nada Mlinarevich, Maureen Hillmann, Mitchell S. V. Elkind, Joy Hirsch, Stephen Dashnaw, Philip M. Meyers, Josh Z. Willey, Edwina McNeill‐Simaan, Veronica Perez, Alberto Canaan, Wayna Paulino‐Hernandez, Gregory J. Zipfel, Katie Vo, Glenn Foster, Andria Ford, Abdullah Nassief, Abbie Bradley, Jannie Serna‐Northway, Kristi Kraus, Lina Shiwani, Nancy Hantler, David S. Liebeskind, Jeffrey Alger, Sergio Godinez, Jeffrey L. Saver, Latisha Ali, Doojin Kim, Matthew Tenser, Michael Froehler, Radoslav Raychev, Sarah Song, Bruce Ovbiagele, Hermelinda Abcede, Peter Adamczyk, Neal Rao, Anil Yallapragada, Royya Modir, Jason Hinman, Aaron Tansy, Mateo Calderon‐Arnulphi, Sunil Sheth, Alireza Noorian, Kwan Ng, Conrad Liang, Jignesh Gadhia, Hannah Smith, Gilda Avila, Johanna Avelar, Frank L. Silver, David Mikulis, Jorn Fierstra, Eugen Hlasny, Leanne K. Casaubon, Mervyn Vergouwen, J. C. Martin del Campo, Cheryl S. Jaigobin, Cherissa Astorga, Libby Kalman, Jeffrey Kramer, Susan Vaughan, Laura Owens, Keith R. Thulborn, Louis R. Caplan, Philip B. Gorelick, Scott E. Kasner, Brett Kissela, Tanya N. Turan, Victor Aletich, Tom P. Jacobs, and Scott Janis
- Subjects
Male ,Time Factors ,Epidemiology ,quantitative magnetic resonance angiography ,Magnetic Resonance Imaging (MRI) ,Cerebral arteries ,Hemodynamics ,Magnetic resonance angiography ,Risk Factors ,Occlusion ,Vertebrobasilar Insufficiency ,blood flow ,magnetic resonance imaging ,Prospective Studies ,Stroke ,Original Research ,Aged, 80 and over ,medicine.diagnostic_test ,Hazard ratio ,Age Factors ,Middle Aged ,Prognosis ,stroke vertebrobasilar disease ,Ischemic Attack, Transient ,Cerebrovascular Circulation ,Cardiology ,Female ,Cardiology and Cardiovascular Medicine ,Blood Flow Velocity ,Adult ,medicine.medical_specialty ,Risk Assessment ,Predictive Value of Tests ,Internal medicine ,medicine ,Humans ,cardiovascular diseases ,Ischemic Stroke ,Aged ,business.industry ,magnetic resonance angiography ,Transient Ischemic Attack (TIA) ,Magnetic resonance imaging ,Blood flow ,medicine.disease ,United States ,Cerebral Angiography ,Cerebrovascular Disease/Stroke ,business - Abstract
Background Atherosclerotic vertebrobasilar disease is a significant etiology of posterior circulation stroke. The prospective observational VER i TAS (Vertebrobasilar Flow Evaluation and Risk of Transient Ischemic Attack and Stroke) study demonstrated that distal hemodynamic status is a robust predictor of subsequent vertebrobasilar stroke risk. We sought to compare predictive models using thresholds for posterior circulation vessel flows standardized to age and vascular anatomy to optimize risk prediction. Methods and Results VER i TAS enrolled patients with recent vertebrobasilar transient ischemic attack or stroke and ≥50% atherosclerotic stenosis/occlusion in vertebral and/or basilar arteries. Quantitative magnetic resonance angiography measured large‐vessel vertebrobasilar territory flow, and patients were designated as low or normal flow based on a prespecified empiric algorithm considering distal territory regional flow and collateral capacity. For the present study, post hoc analysis was performed to generate additional predictive models using age‐specific normalized flow measurements. Sensitivity, specificity, and time‐to‐event analyses were compared between the algorithms. The original prespecified algorithm had 50% sensitivity and 79% specificity for future stroke risk prediction; using a predictive model based on age‐normalized flows in the basilar and posterior cerebral arteries, standardized to vascular anatomy, optimized flow status thresholds were identified. The optimized algorithm maintained sensitivity and increased specificity to 84%, while demonstrating a larger and more significant hazard ratio for stroke on time‐to‐event analysis. Conclusions These results indicate that flow remains a strong predictor of stroke across different predictive models, and suggest that prediction of future stroke risk can be optimized by use of vascular anatomy and age‐specific normalized flows.
- Published
- 2020